DOHMH Roadmap: DALY Estimates

Background

Objective

The objective of this analysis is to estimate DALYs lost in New York City due to the following major categories of conditions (with about 100 conditions in total within these categories):

• Major depression
• Alcohol use
• Marijuana use
• Heroin use
• Cocaine use
• Stimulant use
• Sedative use
• Tranquilizer use

Definition of Key Terms

DALY

Disability-adjusted life years. The DALY is a year of life lived in perfect health and consists of two elements: YLLs and YLDs. The DALY is a measure of overall disease burden, expressed as the number of years lost due to ill-health, disability or early death. It was developed in the 1990s as a way of comparing the overall health and life expectancy of different countries.

\[ DALY = YLL + YLD \]

YLL

Years of life lost. Years of life lost is an estimate of the average years a person would have lived if he or she had not died prematurely.

\[ YLL = (Number\ of\ deaths) * (Standard\ life\ expectancy\ at\ age\ of\ death\ in\ years) \]

YLD

Years of life lost due to disability. This is the morbidity component of the DALY score. To estimate YLD for a particular cause in a particular time period, the number of incident cases in that period is multiplied by the average duration of the disease and a weight factor that reflects the severity of the disease on a scale from 0 (perfect health) to 1 (dead). The basic formula for YLD is the following:

\[ YLD = (number\ of\ incident\ cases) * (disability\ weight) * (average\ duration\ of\ disease) \]

Methods

Data Sources

• 2013 NYCHANES - prevalence estimates
• 2002-2008 NSDUH - drug use prevalence estimates
• 2013 NYC Vital Statistics - mortality estimates
• 2010 Global Burden of Disease Study - national YLD/YLL rates
• 2013 NYC American Community Survey - population estimates

The challenge with using NYCHANES and NSDUH data to estimate the prevalence of a condition is that the n may be too small. To increase their utility of these surveys, we will aggregate age groups into the following strata: childhood (0-14), late adolescence/early adulthood (15-24), adulthood (25-64), and later life (65+).

DALY Estimation

YLLs

To estimate compute NYC YLLs, we will use NYC mortality counts stratified by age, sex, and race. In concodrance with the literature on DALY estimation, life expectancy estimates based on the life expectancy in Japan (82.5 years for women and 80.0 years for men) were used for the calculation of YLL. In order to remain consistent with the methodology of the 2010 Global Burden Disease Study, no age weighting or discounting was applied.

YLDs

To compute NYC YLDs, we will use the two approaches described below:

2005 NYC DOHMH / Michaud (2006)

In order to compare the magnitude of the DALY scores to the 2005 NYC DOHMH study, we will replicate the previous study’s methodology, which was based on Michaud CM, et al. The burden of disease and injury in the United States 1996. Population Health Metrics 2006,4:11.

“For NYC YLD, U.S. Census Bureau population estimates for New York City in 2005 by sex were used to calculate years lived with disability (YLD) by applying national YLD rates and ratios from the Michaud et al. study. If the national YLL:YLD ratio was less than 10, then the NYC YLD was equal to the national YLD:YLL ratio multiplied by NYC YLL. If the national YLD:YLL ratio was greater than or equal to 10 (producing unreliable City estimates), then NYC YLD was equal to the national YLD rate multiplied by the NYC population.”

Implementing the Michaud approach will thus require the following data elements:

• NYC Population by age, sex
• National YLD rates by age, sex
• NYC YLLs by age, sex

In order to remain consistent with the demographic weighting approach used by NYC DOHMH for the 2013 NYCHANES data, NYC population estimates were obtained from the 2013 American Community Survey, which is available on the NYC Department of City Planning website. Since the data from the Michaud study are from 1996 and patterns of disease and disability have changed, we will update the approach using national YLD/YLL rates from the 2010 Global Burden of Disease Study.

Prevalence-based YLDs

Years lived with a disability (YLD) due to each disease can be calculated on the basis of either the incidence or the prevalence of the disease. The initial GBD studies estimated YLD on the basis of the incidence of each disease. Thus, in the 1990 study for example, the YLD estimates measured the future loss of health resulting from disease episodes that began in 1990. One advantage of this approach is that it is consistent with that used for mortality: YLL measure the future loss of life resulting from deaths in a particular year.

The 2010 GBD study adopted the alternative approach and calculated YLD based on the prevalence of the impairments resulting from each disease in the year for which the estimates are made. This approach has the advantage that it assigns YLD to the ages at which they are lived, rather than to the age at which the disease episode that produced them began.

Because prevalence is approximately incidence x duration, prevalence YLD for a condition (across all ages) is approximately the same as the no frills incidence YLD. As such, we can estimate YLDs using the following formula:

\[ YLD = (number\ of\ prevalent\ cases) * (disability\ weight) \]

We can estimate the number of prevalent cases for each condition using survey data from 2013 NYCHANES. Annual prevalence for drug use can be estimated using data from 2002-2008 NSDUH. Disability weights can be extracted from the 2010 Global Burden of Disease study.However, we should note that the prevalence YLD for a condition may be quite different in magnitude to the incidence-based YLD, depending on how age weighting and discounting are applied. As such, comparisons to previous NYC DALY studies should be done with caution.

Further information about estimating DALYs can be found from the Global Burden of Disease concept paper (WHO, 2006).

Disease Rankings

Since our goal is to communicate the burden of diseases in New York City, we will rank each condition in decreasing order of the DALY score. We will also test the stability of the rankings by comparing the results generated from the Michaud approach and the prevalence-based YLDs approach. Moreover, since the 2010 GBD study also provides 95% confidence intervals around point estimates for disability weights and national YLD/YLL rates, further stability checks can be conducted by reporting DALY estimations with their respective upper and lower bounds.

However, we should note that since the DALY estimations are not inclusive of all disease conditions, we will not be able to report our findings as the “top X conditions contributing to DALYs.” Instead, we can only report mental health DALYs in reference to other highly prevalent chronic diseases.

Estimation of Substance Use Dependence

Prevalence estimates of substance use cannot be directly substituted for prevalence of drug dependence or abuse disorders. We make the following assumptions about the average proportion of dependence among users (National Addiction Centre, 2003):

• Alcohol - 15.4%
• Cocaine - 16.7%
• Heroin - 23.1%
• Cannabis - 9.1%

Estimation of Major Depressive Disorder Using PHQ-9

Prevalence estimates for 2-week depression was obtained for 2013 NYCHANES. While 2-week depression prevalence would lead to underestimation of 1-year depression, the use of PHQ-9 scores can also overestimate both MDD and any depressive disorder due to its low positive predictive value (~55%) for PHQ-9 scores below 10, the cutoff between mild and moderate depression (Kroenke, 2002). To adjust for this in the prevalence-based YLD approach, we did not consider PHQ-9 scores below 10 and assumed - from expert opinion - that only half of those with PHQ-9 scores above 10 were actually diagnosed with MDD.

Sensitivity Analysis

In order to validate the Michaud approach, we will use 2005 NYC mortality estimates from the previous DOHMH to test the stability of our DALY rankings. However, since age-weighting is no longer used by the 2010 GBD due to ethical concerns, we suspect the magnitude of 2013 NYC DALYs to be slightly higher than that of the 2005 NYC DALYs.

DALY Estimation

Michaud YLD Approach

This section contains an implementation of the Michaud approach described in the above methods section. We first create a search index containing all the disease conditions of interest.

This search index is then fed through the calculateDALY workhorse function to estimate DALYs for each disease condition. The result is a data.frame object containing the following columns: cause_name, sex, yll, yld, yld_upper, yld_lower, daly, daly_upper, daly_lower.

Prevalence-Based YLD Approach

Similar to the section, we implement the prevalence-based YLD approach here using the same search index.

Results

Michaud YLD Approach

Raw results for this approach can be found under the results directory under the filename nyc_daly_michaud.csv. The file can be opened in Excel and manipulated with a pivot table for aggregation and stratification purposes.

2013 NYC DALY Estimates, Total

cause_name	yll	yld	yld_upper	yld_lower	daly	daly_upper	daly_lower
Ischemic heart disease	142893	13658	19810	8966	156550	162703	151859
Major depressive disorder	0	83953	121100	55076	83953	121100	55076
Other musculoskeletal disorders	2885	74223	89073	58852	77108	91957	61737
Anxiety disorders	0	52051	75105	34951	52051	75105	34951
HIV/AIDS	29554	6239	10198	3244	35793	39752	32798
Chronic obstructive pulmonary disease	12759	21453	34059	11961	34212	46818	24720
Lung cancer	32684	485	883	225	33169	33567	32909
Diabetes mellitus	17422	15059	21862	9929	32481	39284	27351
Asthma	3187	24307	38885	13140	27494	42073	16327
Osteoarthritis	149	26968	41201	16316	27117	41350	16465
Hypertensive heart disease	25274	835	1519	384	26108	26792	25658
Lower respiratory infections	24303	1312	1981	809	25615	26284	25112
High blood pressure	0	23051	31082	15615	23051	31082	15615
Alcohol use disorders	4921	15510	23839	9449	20431	28761	14370
Breast cancer	17147	3054	4732	1956	20201	21880	19103
Bipolar affective disorder	0	16820	25727	10012	16820	25727	10012
Colon and rectum cancers	14606	1055	1774	618	15661	16380	15224
Poisonings	15023	88	230	13	15111	15253	15036
Homicide	14663	NA	NA	NA	14663	NA	NA
Cannabis use disorders	0	14303	21780	8642	14303	21780	8642
Cocaine use disorders	0	13584	24968	6554	13584	24968	6554
Ischemic stroke	0	12250	14808	9752	12250	14808	9752
Cerebrovascular disease	8046	2585	3094	2076	10630	11139	10122
Drug use disorders	2326	6231	8780	4202	8557	11106	6528
Alzheimer’s disease and other dementias	4452	3053	4060	2154	7505	8512	6606
Congenital anomalies	5859	1111	1741	672	6971	7600	6531
Amphetamine use disorders	0	5547	9689	2694	5547	9689	2694
Motor vehicle accidents	3135	512	775	325	3647	3910	3460

• Ischemic heart disease is the leading cause of disease in 2013, but has a wide range of uncertainty
• Disaggregated drug use disorders ranked relatively low, particuarly for non-alcohol-related substances
• Major depressive disorder just missed the top 10 cutoff

2013 NYC DALY Estimates, Male

cause_name	sex	yll	yld	yld_upper	yld_lower	daly	daly_upper	daly_lower
Ischemic heart disease	Male	62241	5253	7628	3433	67494	69869	65674
Major depressive disorder	Male	0	29122	42380	19172	29122	42380	19172
Other musculoskeletal disorders	Male	604	22433	28657	15884	23036	29261	16487
HIV/AIDS	Male	17948	4244	6583	2371	22192	24532	20319
Alcohol use disorders	Male	4438	13308	20434	8139	17747	24873	12577
Lung cancer	Male	17348	238	411	121	17586	17759	17469
Anxiety disorders	Male	0	16888	24380	11291	16888	24380	11291
Chronic obstructive pulmonary disease	Male	5605	10302	16528	5655	15907	22133	11260
Diabetes mellitus	Male	8440	6526	9561	4265	14967	18002	12705
Hypertensive heart disease	Male	11866	268	491	120	12134	12357	11986
Homicide	Male	11903	NA	NA	NA	11903	NA	NA
Asthma	Male	1409	10463	16739	5641	11871	18148	7050
Lower respiratory infections	Male	10657	513	786	311	11170	11443	10968
Poisonings	Male	11035	70	176	12	11105	11210	11047
High blood pressure	Male	0	10872	14946	7183	10872	14946	7183
Osteoarthritis	Male	59	9384	14597	5661	9443	14656	5720
Bipolar affective disorder	Male	0	7449	11473	4414	7449	11473	4414
Colon and rectum cancers	Male	6478	421	680	250	6899	7158	6728
Ischemic stroke	Male	0	5693	6885	4521	5693	6885	4521
Cocaine use disorders	Male	0	4601	8347	2259	4601	8347	2259
Cocaine use disorders	Male	0	4601	8347	2259	4601	8347	2259
Cannabis use disorders	Male	0	4486	6858	2705	4486	6858	2705
Cannabis use disorders	Male	0	4486	6858	2705	4486	6858	2705
Cerebrovascular disease	Male	3085	1042	1250	834	4126	4334	3918
Congenital anomalies	Male	3108	550	855	333	3658	3963	3441
Drug use disorders	Male	1620	1512	2134	1006	3132	3755	2626
Motor vehicle accidents	Male	2060	323	489	206	2383	2549	2267
Alzheimer’s disease and other dementias	Male	1280	832	1114	589	2112	2395	1869
Amphetamine use disorders	Male	0	1711	2950	839	1711	2950	839
Amphetamine use disorders	Male	0	1711	2950	839	1711	2950	839

• Alcohol use disorders rises to the #4 slot
• Homicide and accidental deaths such as poisonings and motor vehicle accidents rise in rankings

2013 NYC DALY Estimates, Female

cause_name	sex	yll	yld	yld_upper	yld_lower	daly	daly_upper	daly_lower
Ischemic heart disease	Female	80652	8404	12182	5533	89056	92834	86184
Major depressive disorder	Female	0	54832	78719	35904	54832	78719	35904
Other musculoskeletal disorders	Female	2281	51790	60415	42969	54071	62696	45250
Anxiety disorders	Female	0	35163	50725	23660	35163	50725	23660
Breast cancer	Female	17147	3054	4732	1956	20201	21880	19103
Chronic obstructive pulmonary disease	Female	7154	11151	17530	6307	18305	24685	13461
Osteoarthritis	Female	90	17585	26605	10655	17674	26694	10745
Diabetes mellitus	Female	8982	8533	12301	5665	17514	21282	14646
Asthma	Female	1779	13844	22146	7499	15623	23925	9277
Lung cancer	Female	15336	247	472	104	15583	15808	15440
Lower respiratory infections	Female	13646	799	1196	498	14445	14841	14144
Hypertensive heart disease	Female	13407	567	1028	264	13974	14436	13671
HIV/AIDS	Female	11606	1995	3615	873	13601	15221	12479
High blood pressure	Female	0	12180	16136	8433	12180	16136	8433
Bipolar affective disorder	Female	0	9371	14254	5598	9371	14254	5598
Colon and rectum cancers	Female	8128	634	1095	368	8762	9223	8496
Ischemic stroke	Female	0	6556	7923	5231	6556	7923	5231
Cerebrovascular disease	Female	4961	1543	1844	1242	6504	6805	6203
Drug use disorders	Female	706	4719	6645	3197	5424	7351	3902
Alzheimer’s disease and other dementias	Female	3172	2221	2946	1565	5393	6118	4737
Poisonings	Female	3988	18	54	1	4006	4042	3989
Congenital anomalies	Female	2751	562	886	339	3313	3637	3090
Homicide	Female	2760	NA	NA	NA	2760	NA	NA
Alcohol use disorders	Female	483	2202	3405	1310	2685	3888	1793
Cannabis use disorders	Female	0	2665	4032	1616	2665	4032	1616
Cannabis use disorders	Female	0	2665	4032	1616	2665	4032	1616
Cocaine use disorders	Female	0	2191	4138	1017	2191	4138	1017
Cocaine use disorders	Female	0	2191	4138	1017	2191	4138	1017
Motor vehicle accidents	Female	1074	189	287	119	1264	1361	1193
Amphetamine use disorders	Female	0	1062	1895	508	1062	1895	508
Amphetamine use disorders	Female	0	1062	1895	508	1062	1895	508

• Breast cancer makes the top 3
• Alzheimer's disease and other dementias ranks very high
• Drug-related disorders get pushed to the bottom

Prevalence-Based YLD Approach

Raw results for this approach can be found under the results directory under the filename nyc_daly_prevalence.csv. The file can be opened in Excel and manipulated with a pivot table for aggregation and stratification purposes.

2013 NYC DALY Estimates, Total

cause_name	yll	yld	yld_upper	yld_lower	daly	daly_upper	daly_lower
Ischemic heart disease	142893	30186	34498	24197	173078	177391	167089
Alcohol use disorders	4921	136164	188737	92528	141085	193658	97450
Major depressive disorder	NA	125830	168883	86154	125830	168883	86154
Other arthritis	NA	88591	123561	59838	88591	123561	59838
Chronic obstructive pulmonary disease	12759	64253	90690	43170	77012	103449	55929
Arthritis	NA	57587	80319	38896	57587	80319	38896
Cocaine use	NA	44665	65691	27916	44665	65691	27916
Breast cancer	17269	24769	34626	16765	42038	51895	34035
Lung cancer	32684	4937	6902	3342	37622	39587	36026
Heroin use	NA	36139	45272	25878	36139	45272	25878
Anxiety	NA	30752	49203	17426	30752	49203	17426
Diabetes mellitus	17422	10119	12143	8095	27541	29565	25517
Cannabis use	NA	24991	34562	16939	24991	34562	16939
Asthma	3187	20058	33430	11143	23245	36617	14331
Colon and rectum cancers	14606	4471	6251	3027	19077	20857	17633
Amphetamine use	NA	8050	11972	4903	8050	11972	4903
Stimulant use	NA	2549	3790	1552	2549	3790	1552
Ischemic stroke	NA	1820	3207	953	1820	3207	953
High blood pressure	NA	0	0	0	0	0	0
Sedative use	NA	0	0	0	0	0	0
Tranquilizer use	NA	0	0	0	0	0	0

• Major depressive disorder ranks number one, beating out the number two slot by almost twice the number of DALYs However, DALY estimates appear to be unstable, taking a wide range of possible values.
• Not enough information to calculate DALY estimates for sedative use, stimulant use, tranquilizer use.

2013 NYC DALY Estimates, Male

cause_name	sex	yll	yld	yld_upper	yld_lower	daly	daly_upper	daly_lower
Alcohol use disorders	Male	4438	72958	101127	49577	77396	105565	54016
Ischemic heart disease	Male	62241	13079	14947	10484	75320	77188	72725
Major depressive disorder	Male	NA	40352	54452	27533	40352	54452	27533
Chronic obstructive pulmonary disease	Male	5605	32495	45865	21833	38100	51470	27438
Other arthritis	Male	NA	31037	43288	20963	31037	43288	20963
Lung cancer	Male	17348	1926	2692	1304	19274	20041	18652
Arthritis	Male	NA	18723	26114	12647	18723	26114	12647
Diabetes mellitus	Male	8440	4770	5724	3816	13210	14164	12256
Cocaine use	Male	NA	12568	18484	7855	12568	18484	7855
Cocaine use	Male	NA	12568	18484	7855	12568	18484	7855
Anxiety	Male	NA	11399	18238	6459	11399	18238	6459
Heroin use	Male	NA	9980	12502	7146	9980	12502	7146
Heroin use	Male	NA	9980	12502	7146	9980	12502	7146
Asthma	Male	1409	7269	12115	4038	8678	13523	5447
Colon and rectum cancers	Male	6478	1835	2565	1242	8313	9043	7720
Cannabis use	Male	NA	8054	11138	5459	8054	11138	5459
Cannabis use	Male	NA	8054	11138	5459	8054	11138	5459
Amphetamine use	Male	NA	2514	3740	1531	2514	3740	1531
Amphetamine use	Male	NA	2514	3740	1531	2514	3740	1531
Stimulant use	Male	NA	1610	2394	980	1610	2394	980
Ischemic stroke	Male	NA	608	1071	318	608	1071	318
Breast cancer	Male	122	0	0	0	122	122	122
High blood pressure	Male	NA	0	0	0	0	0	0
Sedative use	Male	NA	0	0	0	0	0	0
Tranquilizer use	Male	NA	0	0	0	0	0	0

• Alcohol use disorders rises in proportion to major depressive disorder

2013 NYC DALY Estimates, Female

cause_name	sex	yll	yld	yld_upper	yld_lower	daly	daly_upper	daly_lower
Ischemic heart disease	Female	80652	17107	19551	13713	97758	100202	94364
Major depressive disorder	Female	NA	85478	114432	58621	85478	114432	58621
Alcohol use disorders	Female	483	63206	87610	42951	63689	88093	43434
Other arthritis	Female	NA	57555	80274	38875	57555	80274	38875
Breast cancer	Female	17147	24769	34626	16765	41916	51773	33913
Chronic obstructive pulmonary disease	Female	7154	31758	44824	21337	38912	51979	28491
Arthritis	Female	NA	38863	54204	26250	38863	54204	26250
Anxiety	Female	NA	19353	30965	10967	19353	30965	10967
Lung cancer	Female	15336	3011	4210	2038	18347	19546	17374
Asthma	Female	1779	12789	21315	7105	14568	23094	8884
Diabetes mellitus	Female	8982	5349	6419	4279	14331	15401	13261
Colon and rectum cancers	Female	8128	2636	3685	1784	10764	11814	9912
Cocaine use	Female	NA	9765	14361	6103	9765	14361	6103
Cocaine use	Female	NA	9765	14361	6103	9765	14361	6103
Heroin use	Female	NA	8090	10134	5793	8090	10134	5793
Heroin use	Female	NA	8090	10134	5793	8090	10134	5793
Cannabis use	Female	NA	4442	6142	3010	4442	6142	3010
Cannabis use	Female	NA	4442	6142	3010	4442	6142	3010
Amphetamine use	Female	NA	1510	2246	920	1510	2246	920
Amphetamine use	Female	NA	1510	2246	920	1510	2246	920
Ischemic stroke	Female	NA	1212	2136	635	1212	2136	635
Stimulant use	Female	NA	939	1396	572	939	1396	572
High blood pressure	Female	NA	0	0	0	0	0	0
Sedative use	Female	NA	0	0	0	0	0	0
Tranquilizer use	Female	NA	0	0	0	0	0	0

Michaud YLDs vs. Prevalence-Based YLDs: Side-by-Side Comparison

Total

Male

Female

Disease Conditions with Small Sample Sizes

##                    cause_name                      sequlae    sex    age
## 25              Breast cancer                Breast cancer   Male 20-39 
## 26              Breast cancer                Breast cancer   Male 40-59 
## 27              Breast cancer                Breast cancer   Male   60+ 
## 28              Breast cancer                Breast cancer Female 20-39 
## 36                Cocaine use                  Cocaine use Female   60+ 
## 37   Colon and rectum cancers     Colon and rectum cancers   Male 20-39 
## 38   Colon and rectum cancers     Colon and rectum cancers   Male 40-59 
## 39   Colon and rectum cancers     Colon and rectum cancers   Male   60+ 
## 40   Colon and rectum cancers     Colon and rectum cancers Female 20-39 
## 41   Colon and rectum cancers     Colon and rectum cancers Female 40-59 
## 42   Colon and rectum cancers     Colon and rectum cancers Female   60+ 
## 55                 Heroin use                   Heroin use   Male 20-39 
## 56                 Heroin use                   Heroin use   Male 40-59 
## 57                 Heroin use                   Heroin use   Male   60+ 
## 58                 Heroin use                   Heroin use Female 20-39 
## 59                 Heroin use                   Heroin use Female 40-59 
## 60                 Heroin use                   Heroin use Female   60+ 
## 67     Ischemic heart disease       Ischemic heart disease   Male 20-39 
## 70     Ischemic heart disease       Ischemic heart disease Female 20-39 
## 73                Lung cancer                         Lung   Male 20-39 
## 74                Lung cancer                         Lung   Male 40-59 
## 75                Lung cancer                         Lung   Male   60+ 
## 76                Lung cancer                         Lung Female 20-39 
## 77                Lung cancer                         Lung Female 40-59 
## 78                Lung cancer                         Lung Female   60+ 
## 87            Amphetamine use          Methamphetamine use   Male 20-39 
## 88            Amphetamine use          Methamphetamine use   Male 40-59 
## 89            Amphetamine use          Methamphetamine use   Male   60+ 
## 90            Amphetamine use          Methamphetamine use Female 20-39 
## 91            Amphetamine use          Methamphetamine use Female 40-59 
## 92            Amphetamine use          Methamphetamine use Female   60+ 
## 101 Major depressive disorder          moderate depression   Male   60+ 
## 105 Major depressive disorder moderately severe depression   Male 20-39 
## 106 Major depressive disorder moderately severe depression   Male 40-59 
## 107 Major depressive disorder moderately severe depression   Male   60+ 
## 111           Other arthritis              Other arthritis   Male 20-39 
## 125 Major depressive disorder            severe depression   Male 20-39 
## 126 Major depressive disorder            severe depression   Male 40-59 
## 127 Major depressive disorder            severe depression   Male   60+ 
## 128 Major depressive disorder            severe depression Female 20-39 
## 130 Major depressive disorder            severe depression Female   60+ 
## 139           Ischemic stroke              Ischemic stroke   Male 20-39 
## 140           Ischemic stroke              Ischemic stroke   Male 40-59 
## 141           Ischemic stroke              Ischemic stroke   Male   60+ 
## 142           Ischemic stroke              Ischemic stroke Female 20-39

Sensitivity Analysis

2005 NYC DALY Estimates, Total

cause_name	yll	yld	yld_upper	yld_lower	daly	daly_upper	daly_lower
Ischemic heart disease	142893	13658	19810	8966	156550	162703	151859
Major depressive disorder	0	83953	121100	55076	83953	121100	55076
Other musculoskeletal disorders	2885	74223	89073	58852	77108	91957	61737
Anxiety disorders	0	52051	75105	34951	52051	75105	34951
HIV/AIDS	29554	6239	10198	3244	35793	39752	32798
Chronic obstructive pulmonary disease	12759	21453	34059	11961	34212	46818	24720
Lung cancer	32684	485	883	225	33169	33567	32909
Diabetes mellitus	17422	15059	21862	9929	32481	39284	27351
Asthma	3187	24307	38885	13140	27494	42073	16327
Osteoarthritis	149	26968	41201	16316	27117	41350	16465
Hypertensive heart disease	25274	835	1519	384	26108	26792	25658
Lower respiratory infections	24303	1312	1981	809	25615	26284	25112
High blood pressure	0	23051	31082	15615	23051	31082	15615
Alcohol use disorders	4921	15510	23839	9449	20431	28761	14370
Breast cancer	17147	3054	4732	1956	20201	21880	19103
Bipolar affective disorder	0	16820	25727	10012	16820	25727	10012
Colon and rectum cancers	14606	1055	1774	618	15661	16380	15224
Poisonings	15023	88	230	13	15111	15253	15036
Homicide	14663	NA	NA	NA	14663	NA	NA
Cannabis use disorders	0	14303	21780	8642	14303	21780	8642
Cocaine use disorders	0	13584	24968	6554	13584	24968	6554
Ischemic stroke	0	12250	14808	9752	12250	14808	9752
Cerebrovascular disease	8046	2585	3094	2076	10630	11139	10122
Drug use disorders	2326	6231	8780	4202	8557	11106	6528
Alzheimer’s disease and other dementias	4452	3053	4060	2154	7505	8512	6606
Congenital anomalies	5859	1111	1741	672	6971	7600	6531
Amphetamine use disorders	0	5547	9689	2694	5547	9689	2694
Motor vehicle accidents	3135	512	775	325	3647	3910	3460

2005 NYC DALY Estimates, Male

cause_name	sex	yll	yld	yld_upper	yld_lower	daly	daly_upper	daly_lower
Ischemic heart disease	Male	62241	5253	7628	3433	67494	69869	65674
Major depressive disorder	Male	0	29122	42380	19172	29122	42380	19172
Other musculoskeletal disorders	Male	604	22433	28657	15884	23036	29261	16487
HIV/AIDS	Male	17948	4244	6583	2371	22192	24532	20319
Alcohol use disorders	Male	4438	13308	20434	8139	17747	24873	12577
Lung cancer	Male	17348	238	411	121	17586	17759	17469
Anxiety disorders	Male	0	16888	24380	11291	16888	24380	11291
Chronic obstructive pulmonary disease	Male	5605	10302	16528	5655	15907	22133	11260
Diabetes mellitus	Male	8440	6526	9561	4265	14967	18002	12705
Hypertensive heart disease	Male	11866	268	491	120	12134	12357	11986
Homicide	Male	11903	NA	NA	NA	11903	NA	NA
Asthma	Male	1409	10463	16739	5641	11871	18148	7050
Lower respiratory infections	Male	10657	513	786	311	11170	11443	10968
Poisonings	Male	11035	70	176	12	11105	11210	11047
High blood pressure	Male	0	10872	14946	7183	10872	14946	7183
Osteoarthritis	Male	59	9384	14597	5661	9443	14656	5720
Bipolar affective disorder	Male	0	7449	11473	4414	7449	11473	4414
Colon and rectum cancers	Male	6478	421	680	250	6899	7158	6728
Ischemic stroke	Male	0	5693	6885	4521	5693	6885	4521
Cocaine use disorders	Male	0	4601	8347	2259	4601	8347	2259
Cocaine use disorders	Male	0	4601	8347	2259	4601	8347	2259
Cannabis use disorders	Male	0	4486	6858	2705	4486	6858	2705
Cannabis use disorders	Male	0	4486	6858	2705	4486	6858	2705
Cerebrovascular disease	Male	3085	1042	1250	834	4126	4334	3918
Congenital anomalies	Male	3108	550	855	333	3658	3963	3441
Drug use disorders	Male	1620	1512	2134	1006	3132	3755	2626
Motor vehicle accidents	Male	2060	323	489	206	2383	2549	2267
Alzheimer’s disease and other dementias	Male	1280	832	1114	589	2112	2395	1869
Amphetamine use disorders	Male	0	1711	2950	839	1711	2950	839
Amphetamine use disorders	Male	0	1711	2950	839	1711	2950	839

2005 NYC DALY Estimates, Female

cause_name	sex	yll	yld	yld_upper	yld_lower	daly	daly_upper	daly_lower
Ischemic heart disease	Female	80652	8404	12182	5533	89056	92834	86184
Major depressive disorder	Female	0	54832	78719	35904	54832	78719	35904
Other musculoskeletal disorders	Female	2281	51790	60415	42969	54071	62696	45250
Anxiety disorders	Female	0	35163	50725	23660	35163	50725	23660
Breast cancer	Female	17147	3054	4732	1956	20201	21880	19103
Chronic obstructive pulmonary disease	Female	7154	11151	17530	6307	18305	24685	13461
Osteoarthritis	Female	90	17585	26605	10655	17674	26694	10745
Diabetes mellitus	Female	8982	8533	12301	5665	17514	21282	14646
Asthma	Female	1779	13844	22146	7499	15623	23925	9277
Lung cancer	Female	15336	247	472	104	15583	15808	15440
Lower respiratory infections	Female	13646	799	1196	498	14445	14841	14144
Hypertensive heart disease	Female	13407	567	1028	264	13974	14436	13671
HIV/AIDS	Female	11606	1995	3615	873	13601	15221	12479
High blood pressure	Female	0	12180	16136	8433	12180	16136	8433
Bipolar affective disorder	Female	0	9371	14254	5598	9371	14254	5598
Colon and rectum cancers	Female	8128	634	1095	368	8762	9223	8496
Ischemic stroke	Female	0	6556	7923	5231	6556	7923	5231
Cerebrovascular disease	Female	4961	1543	1844	1242	6504	6805	6203
Drug use disorders	Female	706	4719	6645	3197	5424	7351	3902
Alzheimer’s disease and other dementias	Female	3172	2221	2946	1565	5393	6118	4737
Poisonings	Female	3988	18	54	1	4006	4042	3989
Congenital anomalies	Female	2751	562	886	339	3313	3637	3090
Homicide	Female	2760	NA	NA	NA	2760	NA	NA
Alcohol use disorders	Female	483	2202	3405	1310	2685	3888	1793
Cannabis use disorders	Female	0	2665	4032	1616	2665	4032	1616
Cannabis use disorders	Female	0	2665	4032	1616	2665	4032	1616
Cocaine use disorders	Female	0	2191	4138	1017	2191	4138	1017
Cocaine use disorders	Female	0	2191	4138	1017	2191	4138	1017
Motor vehicle accidents	Female	1074	189	287	119	1264	1361	1193
Amphetamine use disorders	Female	0	1062	1895	508	1062	1895	508
Amphetamine use disorders	Female	0	1062	1895	508	1062	1895	508

Discussion

Limitations

There are key limitations to this analysis. First and foremost, the magnitude of the DALY scores should be interpreted and reported with caution. Due to the small sample size of NYC prevalence estimates and the uncertainty around disability weights and national YLL/YLD rates for some conditions, DALY estimates can assume a wide range of values, changing how one condition ranks against the others (for example, alcohol use disorders and diabetes mellitus). For this reason, DALY magnitudes obtained via Michaud approach and the Prevalence-based YLDs cannot be directly compared.

Moreover, the accuracy of DALY estimations suffers from potential biases introduced in the data collection and computation processes. For example, comorbidities with respect to chronic diseases means that DALY estimates based on Vital Statistics mortality counts are overestimating the contribution of YLLs. Summation of prevalence YLDs across all causes can result in overestimation of the total average severity-weighted health state prevalence because of comorbidity between conditions (Mathers, 2006). Over-reporting of some conditions due to misclassification (e.g. where symptoms such as joint pain are labeled as osteoarthritis or occasional wheezing as asthma), under-reporting of undiagnosed conditions (e.g. most mental health problems), and lack of information on condition severity (resulting in high prevalences due to inclusion of very minor conditions or minor symptoms) may also contribute to biased DALY estimates.

In order to convey the uncertainty around our estimates, we visualize the range of values that NYC DALY estimates can take for each condition.

Sensitivity Analysis

NYC DALY rankings and magnitudes using the Michaud approach are fairly consistent using both 2005 and 2013 NYC mortality counts. Moreover, the Michaud approach implemented in this analysis replicated the 2005 NYC DALY estimates from the previous NYC DOHMH study, producing comparable rankings. However, since age-weighting is no longer used due to ethical concerns, the 2013 NYC DALYs are slightly larger in magnitude. Recommendations for future work include running simulations to test the stability of DALY rankings for an even wider range of assumptions.

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